Artificial intelligence and machine learningSay no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original EssayMachine learning is a branch of computer science that allows the computer the ability to learn without being explicitly programmed. Artificial intelligence is the broader concept of machines that can perform tasks in a way that we would consider “intelligent.” Machine learning is a current application of artificial intelligence based on the idea that we should really be able to give machines access to data and let them learn on their own. Uses machine learning One of the most popular uses of artificial intelligence in machine learning, where computers, software, and others act through cognition (like the human brain). Examples of the area where machine learning is heading include the following: –Virtual personal assistantsSiri, Google Now, Alexa, and many others are some of the many popular examples of virtual assistants. As the name says, they try to help in the search for information when asked to find something through voice. All you have to do is ask "what's the weather like today?", when is Manchester United playing" or "set an alarm for 3pm". Machine learning is a very important part of a personal assistant because it collects and refines the information based on your previous encounter with them. Then this set of data is used to get specific results based on your preferences. Virtual assistants are used in a variety of platforms such as smart speakers like Google Home and Amazon Echo, smartphones like Samsung Bixby and Google Pixel like Google Assistant and also mobile apps like Google Video Surveillance Video surveillance is a very difficult and tedious task, but with machine learning, it can be an automated process as they train computers to handle this task crime by simply monitoring unusual behavior using machine learning. Social media Social media such as Facebook, Twitter, Instagram and many others use machine learning to personalize the news feed, adds and much more. In applications such as camera use facial recognition to identify people in a specific scene and also identify their faces in order to add effects such as smoothing their face. Machine learning is also used in apps like Facebook to identify people we may know and suggest we add them as our friends. Additionally, apps like Pinterest use computer vision to find objects in images and suggest similar pins accordingly. Filtering spam and malware through email Apps like Gmail use machine learning to classify email into primary, social, important, and spam. This is done with the help of filtering done behind the scenes using machine learning. Over 325,000 pieces of malware are detected every day, and each piece of code is 90-98% similar to previous versions. The ML-based security program understands the coding model. Online Customer Support Microsoft bots are used to provide chat rooms where people can report on the services they get and this is due to machine learning. Likewise when a browser opens the search is customized for that specific person. For example, YouTube is highly personalized to each person based on what they prefer to watch thanks to machine learning. Product RecommendationsWhen you buy something online you start receiving emailsrelated to that product in other stores and when you browse online you see some sites that suggest things to buy that are close to your tastes. This is due to machine learning picking up your likes and dislikes as you browse the internet combined with an algorithm working under the hood. Fraud Detection Online fraud detection is among the frontiers that machine learning is tackling head-on in trying to analyze illegal online transactions and prevent money laundering, such as PayPal. This is done using a set of tools that can help compare millions of transactions that have occurred and distinguish between legitimate and illegal transactions. Introducing Machine Learning into Smartphones The first telephone was made by Alexander Graham in 1876 and became a revolutionary gadget as 1900 approached The telephone was used for basic services such as calling and texting in the late 20th century. As the years passed, the phone transformed from a basic phone to a mobile phone and then to a smartphone introduced in 2000, for example, Sony Ericson R380. This was a revolutionary idea at the time as it featured a capacitive touchscreen, something that had never been seen before on a phone. When the momentum of smartphones started and many companies joined i.e. Apple, Android and many more. Due to the demand for new features, the smartphone industry has tried to outdo each other and, in the process, sell more. This has led the companies that produce the phone to invest hugely in research and development in order to present new features. Artificial intelligence has always been a new frontier for the phone but computing power has always been a constraint. The computing power of smartphones cannot be sufficient to train models necessary for the learning process of an artificial intelligence. Training a model involves feeding a lot of data to that model until it can recognize certain data. This is burdensome for a smartphone which has low computing power and so the training is done on a workstation and once done is then brought back to the device via tensorflowframework.TensorflowTensorflow an open source software library for flow programming data across a wide range of tasks. The main tasks are its application in a neural network that serves as the basis for training data models. It is mainly used by Google in machine learning which it provides across its range of applications, for example the Google Keyboard which has predictive typing. Tensorflow is a lightweight library perfect for smartphones. In May 2017 Google released tensorflowlite whose main goal is to provide lightweight Android smartphones with machine learning (specifically Android 8.0 Oreo). The core of thickflow is programmed in c++. A research design is a blueprint of methods and procedures used to collect and analyze variables when conducting a research study. A specific question suitable for study in a research project should be considered and then an appropriate method for conducting the research should be chosen. This is important for effective coverage of the highlighted objectives and completion of the research. The research data was collected through participant observation, such as using senses such as the eyes, examining people in a target population. There was also the case of examining previous documents on artificial intelligence from which we have valuable information relating to the birth of this technology. The target population involves the people I want to collect information from and, in mycase, involves any person who owns a smartphone. Features like predictive typing that involves using the Google keyboard will be an easy task. It is also called observational study and is a method of obtaining evaluative information that involves an evaluator observing his subject in his place of living and without changing the environment. This type of data collection is used in conjunction with other data collection procedures, such as surveys, questionnaires, etc. The main purpose is to evaluate a behavioral process, an event or when results can be seen. When observing the subject you should not make him aware of your purpose as this can alter the observation and for this reason the subject should not be aware. There are two types of direct observation: structured direct observation and unstructured direct observation. Structured direct observation is used when we want to obtain standardized information and obtain quantitative data while unstructured direct observation involves observing natural events and obtaining qualitative data. This involves looking at the features some smartphones offer, ranging from facial detection in photos to predictive typing in keyboards. When you use the Google keyboard, you learn a person's typing patterns and distinguish the words a person types. This intern stores those words in a database and later reproduces them when writing the text of a Facebook post. Online data collection was among the primary research methodology used to obtain this information. Sending interviews online can be tricky as the evaluator and participant have never met, making it very difficult to share private information. Therefore, you must first find ways for the participant to trust you and agree to share that information. It is estimated that more than 80% of all households in the United States now have a computer at home, and of these, nearly 92% have the Internet. access. As computers became more prevalent in American society, the next natural progression in communication came through the Internet. This increasing trend is due to the invention of smartphones. Smartphone features are the main selling point today, that is, the one who outwits the other in terms of providing better features that the customer is willing and capable of for such a smartphone, then gets the day. Apple, a technology company, is a leading competitor in this field, innovating every year to produce gadgets that have impressed everyone and this has created a group of apple supporters. They are willing to spend more than $1000 for a smartphone. The company's latest innovation is powered by machine learning to provide security to its flashy iPhone , it would not have been possible to achieve it. Machine learning involves training your computer to think like a person without explicitly coding it. This would then involve training a model by showing it a lot of data and then being able to make hypotheses about that specific data. imagine how you can code a program that distinguishes between apple and oranges, it could be argued that you can by saying that apple an apple is between red and brown and orange is yellow and then you can develop a program that analyzes the pixel in those images and if the color coincides with the color yellow. This may be true, but what about if the program is fed by black and white photos, then the program cannot determine this. This is where it comes in,.